Mathbabe (so far)
Mathbabe (so far)
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Mathbabe (so far)

Last updated on 2013-04-30

About the Book

About the Author

Table of Contents

  • Chapter One
  • June 2011
  • Women on S&P500 boards of directors
  • July 2011
  • Bank accounting link
  • Motivating transparency: what we could do about too big to fail
  • I love math nerd kids
  • What is an earnings surprise?
  • Math contests kind of suck
  • High frequency trading
  • High frequency trading: Update
  • Love you people
  • Follow up on: math contests kind of suck
  • What tensor products taught me about living my life
  • Happiest being sad
  • Measuring historical volatility
  • The Bad Food Tax
  • Quit your job and become a data miner!?
  • Elizabeth Warren: Moses and the Promised Land
  • Is too big to fail a good thing?
  • Historical volatility on the S&P index
  • !/usr/bin/env python
  • Three strikes against the mortgage industry
  • What kind of math nerd job should you have?
  • August 2011
  • Why didn’t anybody invite me!?
  • Cool example of Bayesian methods applied to education
  • How do you disagree?
  • June 2011
  • Women on a board of directors: let’s use Bayesian inference
  • !/usr/bin/env python
  • plot prior distribution:
  • compute likelihoods for each of the 11 possible ratios of women:
  • plot unscaled posterior distribution:
  • plot scaled posterior distribution:
  • August 2011
  • Some R code and a data mining book
  • Why should you care about statistical modeling?
  • Adam Smith made me buy a Kindle
  • Data Viz
  • Monday morning reading list
  • Wall Street versus us
  • The Life Cycle of a Hedge Fund
  • Open Source Ratings Model?
  • Open Source Ratings Model (Part 2)
  • Are Corporations People?
  • Default probabilities and recovery rates
  • I.P.O. pops
  • What’s with errorbars?
  • How the Value-Added Model sucks
  • Is willpower a quantifiable resource?
  • Machine learners are spoiled for data
  • Karaoke
  • Demographics: sexier than you think
  • Want my advice?
  • Should short selling be banned?
  • Lagged autocorrelation plots
  • What is the mission statement of the mathematician?
  • We didn’t make money on TARP!
  • Why log returns?
  • Strata data conference
  • September 2011
  • Good for the IASB!
  • I don’t want to live forever
  • Back!
  • The reckoning
  • What is “publicly available data”?
  • Guest post: The gold standard
  • Some cool links
  • Debt
  • Meetups
  • Working with Larry Summers (part 3)
  • Monday morning links
  • What are the chances that this will work?
  • The pandas module and the IPython notebook
  • Politics: the good news and the bad news
  • Guest Post: What is a family?
  • Household debt amnesty?
  • What the hell is going on in Europe?
  • How do you standardize tests?
  • Back from Strata Jumpstart
  • Do higher taxes kill jobs?
  • Are SAT scores going down?
  • In German beard circles, tensions are high.
  • I never sit on the subway
  • Why and how to hire a data scientist for your business
  • June 2011
  • Guest post: Tax Repatriation Day
  • Did someone say regulation?
  • July 2011
  • Weekend Reading
  • September 2011
  • The flat screen TV phenomenon
  • Occupy Wall Street—Report
  • Never apologize
  • Go Rays!
  • Occupy Wall Street: Day 13
  • October 2011
  • Mortar Hawk: hadoop made easy
  • Is the Onion actually America’s finest news source?
  • First day of calculus class
  • “Our organization does not reward failure” – Koch
  • Data science: tools vs. craft
  • My friend the coffee douche
  • Bayesian regressions (part 1)
  • Financial Terms Dictionary
  • Habits
  • Saturday afternoon quickie
  • What’s wrong with Wall Street and what should be done about it?
  • Koo: don’t be surprised by the crappy economy
  • Bayesian regressions (part 2)
  • Occupy Wall Street flyer
  • Wall Street and the protests
  • Data Without Borders: datadive weekend!
  • NYCLU: Stop Question and Frisk data
  • Datadive update
  • What is a Credit Union? (#OWS)
  • Alternative Banking System
  • David Graeber on Occupy Wall Street
  • Topology of financial modeling
  • Some really terrible ideas
  • Math in Business
  • What are the options?
  • Cultural Differences
  • Mathematical Differences
  • Which jobs are good for women?
  • How do I get a job like that?
  • Why Credit Unions? (#OWS) (part 1)
  • Credit Unions are not Too Big To Fail
  • Volker Rule/Glass Steagall
  • Lobbying—just as bad?
  • Credit Unions in NYC flyer
  • Shareholder Value
  • Emanuel Derman’s Models.Behaving.Badly.
  • What’s your short list of actionable complaints?
  • Is Big Data Evil?
  • Open Forum next Friday
  • Data Science and Engineering at Columbia?
  • #OWS Alternative Banking meeting today
  • #OWS Alternative Banking update
  • November 2011
  • Towards a better financial system
  • Quantitative tax modeling?
  • #OWS meeting tomorrow
  • Open Forum speeches
  • The Numbers are in: Round 1 to #OWS
  • Why I’m involved with #Occupy Wall Street
  • Truth Values
  • Gaming the system
  • June 2011
  • Working with Larry Summers (part 1)
  • Working with Larry Summers (part 2)
  • November 2011
  • In praise of nerd kids
  • #Occupy Wall Street meeting and news
  • Overfitting
  • The sin of debt
  • Postage paid protest
  • Morning poem
  • Hey Google, do less evil.
  • Zuccotti Park just now: updated
  • In memory of Sally Hale
  • Protest today
  • Occupy the SEC: commenting on the Volcker Rule
  • Alternative Banking meeting today
  • What does “too big to fail” mean?
  • Who takes risks?
  • What’s the Volcker Rule?
  • ‘Move Your Money’ app (#OWS)
  • Sing with me! (#OWS)
  • Two poems
  • No gifts, please
  • Regulation arbitrage, the Volcker Rule, and TBTF (#OWS)
  • Two pieces of good news
  • Correlated trades
  • December 2011
  • Various #OWS links
  • Hank Paulson
  • Quantitative theory of blogging
  • Crowdsourcing projects
  • Good bank/ bad bank – why we didn’t do it
  • #OWS data nerd
  • ISDA has a blog!
  • Meritocracy and horizon bias
  • Thank you, Inside Job
  • Resampling
  • Conservation Law of Money
  • The sin of debt (part 2)
  • Privacy vs. openness
  • Where is Volcker’s letter? (#OWS)
  • What up, New York Times? (#OWS)
  • Bloomberg engineering competition gets exciting
  • A rising tide lifts which boats?
  • Bloomberg engineering competition goes to Cornell
  • How to challenge the SEC
  • Why work?
  • Need your vote
  • Crappy modeling
  • Steam queen
  • A good data scientist is hard to find
  • Is Stop, Question and Frisk racist?
  • Economist versus quant
  • December 2011
  • Information loss
  • Matt Stoller explains politics
  • A New Year’s resolution you can keep
  • January 2012
  • The sin of debt (part 3)
  • #Occupy Wall Street course at Columbia University
  • Differential privacy
  • Ken Ribet’s love note from Serge Lang
  • Politics of teacher pay disguised as data science
  • It takes imagination to be boring
  • Who the hell is buying European debt?
  • #Occupy Wall Street course at Columbia University: update
  • #OWS news
  • CBC Radio
  • The Waltons’ money
  • Open Models (part 1)
  • Happy Baconmas!
  • Shareholder value and Adam Smith
  • High Frequency Trading and Transaction Taxes
  • Sunday Links
  • Puzzle blog
  • Quantitative analysis of regulatory capture
  • Happy Birthday, Betty White!
  • Change academic publishing
  • Followup: Change academic publishing
  • How’s it going with the Volcker Rule?
  • Apologies to Adam Smith
  • Bad statistics debunked: serial killers and cervixes
  • Data Scientist degree programs
  • Seasonally adjusted news
  • Occupy the World Economic Forum
  • Mortgage settlement talks
  • Brainstorming with narcissists
  • Updating your big data model
  • WTF: Greek debt vs. CDS
  • Sturgeon
  • Does hip-hop still exist?
  • “Where to start?”, I wondered.
  • Complexity and transparency in finance
  • Medical identifiers
  • Freddie Mac: worse than hedge funds?
  • Econned and Magnetar
  • February 2012
  • Alternative Banking in FT Alphaville (#OWS)
  • CDS data and open source ratings
  • Let them game the model
  • The SEC needs handcuffs
  • Data Science needs more pedagogy
  • Raise capital gains and stop flying
  • Women in math
  • Opacity, noise, and overpopulation in finance
  • Preggers
  • February 2012
  • Politicians and insider trading
  • More Money than God
  • This month’s Sky Mall: a sneak peek
  • #OWS upcoming events
  • As predicted: watered down insider trading bill
  • The future of academic publishing
  • What’s going on: Greece and mortgages
  • How unsupervised is unsupervised learning?
  • New online course: model thinking
  • Mathematics has an Occupy moment
  • Today is Volcker Day
  • How Big Pharma Cooks Data: The Case of Vioxx and Heart Disease
  • A modeled student
  • How Harvard is failing its students
  • ECB trades crap for slightly less crappy crap
  • Sunday morning music videos
  • Why I love nerds
  • What data science should be doing
  • Creepy model watch
  • #OWS Alternative Banking update
  • Model Thinking (part 2)
  • It’s all mom’s fault
  • I am the most boring person in the world
  • New favorite band: Unbunny
  • Teaching scores released
  • Math teaching needs overhaul
  • Math-Startup Collaborative at Columbia tomorrow
  • Vikram Pandit: let’s talk
  • Economists don’t understand the financial system
  • March 2012
  • Open Models (part 2)
  • This is water
  • Charity auctions and hate crimes
  • Do not track vs. don’t track
  • Why experts?
  • The Value Added Teacher Model Sucks
  • Versus what?
  • Quants for the rest of us
  • Sausage Wall
  • VAM versus what?
  • Why Larry Summers lost the presidency of Harvard
  • Hip Hop’s Cambrian Explosion: Part 1
  • Interlude: Newt Haiku
  • Hip Hop’s Cambrian Explosion: Part 2
  • Interlude: Egret Ardor
  • Propaganda with a Caveat
  • Hip Hop’s Cambrian Explosion: Part 3
  • Calligraphy of geese
  • Recruiting against Goldman Sachs
  • Which muppet are you?
  • Supply side economics and human nature
  • March 2012
  • The higher education bubble
  • Today is Sonia Kovalevsky Day
  • The Market Price of Privacy
  • I regret nothing
  • Random stuff, some good some bad
  • Bloomberg joins Occupy Wall Street
  • On NPR’s Morning Edition (#OWS)
  • How informed does an opinion have to be before it’s taken seriously?
  • What’s Mahout?
  • Vote with your wallet
  • Parents: don’t put your kid on a diet
  • April 2012
  • What is innovation?
  • The muppets strike back
  • Who here reads Dutch? (#OWS)
  • Thought experiment: witness protection program
  • It sucks to be rich
  • More creepy models
  • Who is the market?
  • On the making of a girl nerd
  • Continuously forecasting
  • In which mathbabe becomes insurance claims adjuster
  • Calling all data scientists! The first ever global data science hackathon
  • How to teach someone how to prove something
  • Should we have a ratings agency for scientific theories?
  • #OWS update: looking for UX help
  • Get overpaid so people will listen to you
  • The Great Wealth Transfer, late 1900′s to early 2000′s (part 1)
  • Can clouds think?
  • Reputational risk is insufficient for ratings agencies
  • Powerpoint kills me from within my soul
  • Are politicians failing our lobbyists? (Onion news)
  • What’s fair?
  • Occupy Wall Street isn’t dead
  • Fox News fabricates a part of Obama’s speech
  • Online learning promotes passivity
  • Declaration of Linear Independence: the nerdiest thing you’ve ever seen
  • Hey, Doocy apologized for fabricating part of Obama’s speech!
  • Innovation, elevation, and space travel
  • In Denial (#OWS)
  • The Addiction (#OWS)
  • An Intervention (#OWS)
  • NYC Data Hackathon
  • Conclusion (#OWS)
  • May 2012
  • It’s May Day!
  • The student debt crisis
  • Occupy Data!
  • Great news for NYC dataphiles: Microsoft Research is coming to NYC
  • Being a single mom is not a crime
  • The meritocracy myth
  • Performing tomorrow night with Reno
  • May 2012
  • How are you a narcissist?
  • To my Libertarian friends
  • Privacy concerns
  • Evil finance should contribute to open source
  • Conspiracy theorists may be right but they can’t explain why
  • Ideas for two thesis problems in data science
  • Who wants Jamie Dimon’s job?
  • Tech firm mindset to avoid like the plague
  • The modeling death spiral for public schools
  • Stop with the man-diets already, coffee is good for you.
  • Recovery begins when addiction ends: an open letter to Jamie Dimon (#OWS)
  • Google’s promotion policy sucks for women
  • WTF with girdles?!?
  • Stop, Question, and Frisk policy getting stopped, questioned, and frisked
  • Buying organic doesn’t make you better than me
  • An open source credit rating agency now exists!
  • The engaged skeptic
  • Favorite bands
  • All the good data nowadays is private – what’s the point of having a data science Ph.D.?
  • Everybody lies (except me)
  • Biking in New York City
  • When “extend and pretend” becomes “delay and pray”
  • How to talk conservative
  • Best case/ worst case: Medicine 50 years from now
  • June 2012
  • One language to rule them all
  • A low Fed rate: what does it mean for the 99%?
  • An easy way to think about priors on linear regression
  • Combining priors and downweighting in linear regression
  • Regulation is not a dirty word
  • Who will Regulate the Superheroes on Wall Street?
  • What if the bond markets priced in actual risk?
  • Hangover cure
  • Personal Democracy Hackathon today
  • The fake problem of fake geek girls, and how to be a sexy man nerd
  • Happy Birthday to me!
  • I don’t trust politicians more than I trust bankers
  • Questions for Jamie Dimon
  • Using retirement money now
  • My followership problem
  • Germany’s risk
  • On being an alpha female
  • Stop and Frisk silent march today
  • Jamie Dimon gets a happy ending massage at Banking Committee hearing
  • Who should be on the Fed Bank Boards? #OpenFed
  • Please don’t have any kids
  • Quants, Models, and the Blame Game
  • Saturday morning reading
  • Is science a girl thing?
  • Coding is like being in a band
  • Why are pharmaceutical companies allowed to do their own trials?
  • June 2012
  • The basic unit is risk
  • Free online classes: the next thing
  • Is a $100,000 pension outrageous?
  • Analemma
  • July 2012
  • Mixing colors: pigment vs. light
  • How much of data science is busy work?
  • HCSSiM workshop day 1
  • HCSSiM Workshop day 2
  • HCSSiM Workshop day 3
  • Nim
  • HCSSiM Workshop day 4
  • HCSSiM Workshop day 5
  • HCSSiM Workshop day 6
  • Toilet paper rant
  • Center for Popular Economics Summer Institute 2012
  • HCSSiM Workshop day 7
  • HCSSiM Workshop day 8
  • Mathematicians know how to admit they’re wrong
  • HCSSiM Workshop day 9
  • How to lie with statistics, Merck style
  • HCSSiM Workshop day 10
  • It rocks to be 40
  • HCSSiM Workshop, day 11
  • HCSSiM Workshop, day 12
  • Yellow Pig Carols
  • HCSSiM Workshop, day 13
  • HCSSiM Workshop, day 14
  • HCSSiM Workshop day 15
  • HCSSiM Workshop day 16
  • HCSSiM Workshop day 17
  • Exploit me some more please
  • Tu-du leest bork bork
  • A call to Occupy: we should listen.
  • Today is a day for politics
  • Is open data a good thing?
  • Why is LIBOR such a big deal? (#OWS)
  • Income distributions and misleading poll questions (#OWS)
  • Does mathematics have a place in higher education?
  • The douche burger, and putting a ruler to the dick.
  • Columbia Data Science Institute: it’s gonna happen
  • Statisticians aren’t the problem for data science. The real problem is too many posers
  • August 2012
  • Gangnam Style
  • VAM shouldn’t be used for tenure
  • Why the internet is creepy
  • Le Monde article (#OWS)
  • Bailout, the book
  • What is a proof?
  • I love whistleblowers
  • High frequency trading: does it hurt the little guy?
  • Looterism
  • August 2012
  • Datadive weekend with DataKind September 7-9
  • Subway etiquette: applying makeup on the 1 train
  • Away for a week – will miss you
  • Update on organic food
  • Another death spiral of modeling: e-scores
  • The U.S. Treasury is a bad baby daddy
  • Someone didn’t get the memo about regulatory capture
  • When to quit your nerd job
  • Explain your revenue model to me so I’ll know how I’m paying for this free service
  • NSA mathematicians
  • #OWS update
  • What makes us fat
  • The country is going to hell, whaddya gonna do.
  • School starts next week
  • Citigroup’s plutonomy memos
  • Automated call centers and superorganisms
  • September 2012
  • Stuff you might want to know about
  • Fair versus equal
  • Women, marriages, and the rat-race
  • STEM jobs and the economy
  • 52 Shades of Greed cards fundraiser now up: please help! (#OWS)
  • Videos and a love note
  • Columbia data science course, week 1: what is data science?
  • How is math used outside academia?
  • Datadive: NYC Park data
  • NYC Parks datadive update: does pruning prevent future fallen trees?
  • Yesterday
  • Pruning doesn’t do much
  • Columbia data science course, week 2: RealDirect, linear regression, k-nearest neighbors
  • Why are the Chicago public school teachers on strike?
  • Occupy Wall Street is one year old
  • The Debt Resistors’ Operation Manual
  • Emanuel Derman’s Apologia Pro Vita Sua
  • Two rants about hiring a data scientist
  • We are the 47%
  • Am I the sexiest thing about the 21st century?
  • Columbia Data Science course, week 3: Naive Bayes, Laplace Smoothing, and scraping data off the web
  • Filter Bubble
  • Evaluating professor evaluations
  • Columbia Data Science course, week 4: K-means, Classifiers, Logistic Regression, Evaluation
  • What is a model?
  • A Few Words on the Soul
  • Telling people to leave finance
  • October 2012
  • High frequency trading: how it happened, what’s wrong with it, and what we should do
  • Student loans are a regressive tax
  • Bad news wish list
  • Knitting porn
  • Next-Gen Data Scientists
  • Columbia Data Science course, week 5: GetGlue, time series, financial modeling, advanced regression, and ethics
  • Dissolve the SEC
  • October 2012
  • The Neighbors
  • Suresh Naidu: analyzing the language of political partisanship
  • Neil Barofsky on the Fed Stress Test
  • Live and let live, motherfuckers
  • Columbia Data Science course, week 6: Kaggle, crowd-sourcing, decision trees, random forests, social networks, and experimental design
  • Personal privacy and institutional transparency
  • Philanthropy can do better than Rajat Gupta
  • The investigative mathematical journalist
  • Gaming the Google mail filter and the modeling feedback loop
  • Causal versus causal
  • Growing old: better than the alternatives
  • Columbia Data Science course, week 7: Hunch.com, recommendation engines, SVD, alternating least squares, convexity, filter bubbles
  • What’s a fair price?
  • Birdwatching
  • Amazon’s binder reviews
  • Are healthcare costs really skyrocketing?
  • We’re not just predicting the future, we’re causing the future
  • How to measure a tree
  • Strata: one down, one to go
  • For the nerds: what’s wrong with this picture?
  • On my way to AGNES
  • Columbia Data Science course, week 8: Data visualization, broadening the definition of data science, Square, fraud detection
  • An AMS panel to examine public math models?
  • The definitive visualization for Hurricane Sandy, if you’re a parent of small children
  • Occupy in the Financial Times
  • November 2012
  • Columbia Data Science course, week 9: Morningside Analytics, network analysis, data journalism
  • Hubbard the economic whore
  • Ask Aunt Pythia
  • The zit model
  • The NYC subway, Aunt Pythia, my zits, and Louis CK
  • Money market regulation: a letter to Geithner and Schapiro from #OWS Occupy the SEC and Alternative Banking
  • OWS working groups Occupy the SEC and Alternative Banking have released an open letter to Timothy Geithner, Secretary of the U.S. Treasury, and Mary Schapiro, Chairman of the SEC, calling on them to put into place reasonable regulation of money market funds (MMF’s).
  • When are taxes low enough?
  • Columbia Data Science course, week 10: Observational studies, confounders, epidemiology
  • Medical research needs an independent modeling panel
  • Aunt Pythia’s advice
  • Free people from their debt: Rolling Jubilee (#OWS)
  • Anti-black Friday ideas? (#OWS)
  • Data science in the natural sciences
  • The ABC Conjecture has not been proved
  • Columbia Data Science course, week 11: Estimating causal effects
  • O’Reilly book deal signed for “Doing Data Science”
  • Aunt Pythia’s advice
  • Support Naked Capitalism
  • Whither the fake clicks?
  • Columbia Data Science course, week 12: Predictive modeling, data leakage, model evaluation
  • Black Friday resistance plan
  • A primer on time wasting
  • It’s Pro-American to be Anti-Christmas
  • Aunt Pythia’s advice and a request for cool math books
  • Systematized racism in online advertising, part 1
  • November 2012
  • On Reuters talking about Occupy
  • How to evaluate a black box financial system
  • Rolling Jubilee is a better idea than the lottery
  • Columbia Data Science course, week 13: MapReduce
  • How to build a model that will be gamed
  • December 2012
  • Aunt Pythia’s advice
  • How do we quantitatively foster leadership?
  • Diophantus and the math arXiv
  • Can we put an ass-kicking skeptic in charge of the SEC?
  • Unequal or Unfair: Which Is Worse?
  • How math departments hire faculty
  • Aunt Pythia’s advice
  • Costco visit
  • Columbia Data Science course, week 14: Presentations
  • Fighting the information war (but only on behalf of rich people)
  • When accurate modeling is not good
  • MOOC is here to stay, professors will have to find another job
  • MOOCs and calculus
  • Aunt Pythia’s advice
  • Silicon Valley: VC versus startup culture
  • Making math beautiful with XyJax
  • If Barofsky heads the SEC I’ll work for it
  • Empathy, murder, and the NRA
  • Nate Silver confuses cause and effect, ends up defending corruption
  • Whom can you trust?
  • Consumer segmentation taken to the extreme
  • Corporations don’t act like people
  • Suggested New Year’s resolution: start a blog
  • Open data is not a panacea
  • On trusting experts, climate change research, and scientific translators
  • I totally trust experts, actually
  • January 2013
  • Is mathbabe a terrorist or a lazy hippy? (#OWS)
  • Open data and the emergence of data philanthropy
  • Planning for the robot revolution
  • I wish I knew now what I’ll know then
  • Aunt Pythia’s advice
  • Sunday (late) morning reading list
  • I don’t have to prove theorems to be a mathematician
  • The complexity feedback loop of modeling
  • Data Science explained by the media, or: why I might just screw your wife while you’re at work
  • Data scientists and engineers needed for a weekend datafest exploring money and politics
  • At the JMM
  • Aunt Pythia’s advice
  • Leaning into the pain
  • Should the U.S. News & World Reports college ranking model be open source?
  • ThoughtWorks
  • Quantifying the pull of poverty traps
  • R is mostly like python but sometimes like SQL
  • Alt-Banking calls on Senate to defend Main Street against Wall Street (#OWS)
  • Aunt Pythia’s advice
  • January 2013
  • The Yarn Whisperer
  • Google search is already open source
  • The Compliment Gang
  • The senseless war between business and IT/data
  • I love me some nerd girls
  • Sentiment should not be the new horizon in journalism
  • Aunt Pythia’s advice
  • Advice for young women math professors
  • This is what it feels like to be a snob
  • Bill Gates is naive, data is not objective
  • Money in politics
  • Singularity Institute and Google: what are their plans?
  • February 2013
  • The Sandy Hook Project
  • Aunt Pythia’s advice
  • Barry Mazur wins the National Medal of Science
  • Links to videotaped talks and pdf slides
  • HSBC Valentine’s Day action (#OWS)
  • Bad model + high stakes = gaming
  • It’s not that I don’t understand you, it’s that you’re wrong
  • Looking for ideas for a mathbabe logo
  • Aunt Pythia’s advice
  • Gender bias in math
  • Occupy HSBC: Valentine’s Day protest at noon #OWS
  • Johnson Research Labs
  • The smell test for big data
  • There should be a macho way to say “I don’t know”
  • HSBC protest yesterday (#OWS)
  • Aunt Pythia’s advice
  • Phenomenal woman
  • Five false myths that make liberals feel good
  • Good news for professors: online courses suck
  • Mathbabe t-shirts for sale!
  • NYC data hackathons, past and future: Politics, Occupy, and Climate change (#OWS)
  • Break up the megabanks already (#OWS)
  • Aunt Pythia’s advice
  • The overburdened prior
  • Ninja Warrior – Sasuke
  • Rachel Schutt speaks at Strata tomorrow about Next-Gen data science
  • How much are the taxpayers subsidizing too-big-to-fail banks, if not $83 billion per year?
  • Is mathematics a vehicle for control fraud?
  • March 2013
  • Prices in the junk bond market
  • Aunt Pythia’s advice
  • Nasty reader comments and blogging
  • HSBC Action today at noon
  • A blogging parliament
  • WTF happened to feminism?!
  • Poseurs should not own the backlash against data science poseurs
  • Unintended Consequences of Journal Ranking
  • Aunt Pythia’s advice
  • Modeling fraud in the financial system
  • March 2013
  • Team Turnstile: how do NYC neighborhoods recover from extreme weather events?
  • Black Scholes and the normal distribution
  • I kind of hate TED talks
  • “The problem here is not the message. The problem is the messenger.”
  • Data audits and data strategies
  • Aunt Pythia’s advice – sex edition
  • Modeling in Plain English
  • Data science code of conduct, Evgeny Morozov
  • Guest Post SuperReview Part I of VI: The Occupy Handbook
  • Guest Post SuperReview Part II of VI: The Occupy Handbook Part I: How We Got Here
  • Guest Post SuperReview Part III of VI: The Occupy Handbook Part I and a little Part II: Where We Are Now
  • Guest Post SuperReview: Intermezzo
  • Aunt Orthoptera: Advice from an Arthropod
  • Intermezzo II
  • Hackprinceton
  • Nerd Nite: A Drunken Venue for Ideas
  • Leila Schneps is a mystery writer!
  • WTF is happening in Cyprus?
  • Papers I’ve been reading lately
  • Aunt Pythia’s advice
  • Value-added model doesn’t find bad teachers, causes administrators to cheat
  • April 2013
  • Giving isn’t the secret
  • Guest post: Divest from climate change
  • We don’t need more complicated models, we need to stop lying with our models
  • K-Nearest Neighbors: dangerously simple
  • Guest post by Julia Evans: How I got a data science job
  • Aunt Pythia’s advice
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